Search Results (30,452)

Background/Objectives: Polypharmacy is common in elderly nursing home residents (NHR), due to the high prevalence of chronic diseases. This practice increases the risk of clinically significant drug–drug interactions (DDIs) with serious consequences for patient health and safety. The objective of this study was to evaluate the prevalence of DDIs using the UpToDate Drug–Drug Interaction Checker, potentially inappropriate medication (PIM, as defined by the STOPP-START criteria), and their association with major clinical outcomes. Methods: Demographic data, clinical history and detailed medication records of 275 patients from Romania were collected. Potentially inappropriate medications were identified using 16 selected criteria from the 2023 STOPP/START guidelines. Statistical analysis was performed using GraphPad, R, and Python, involving Chi-squared and Fisher’s exact tests with Benjamini–Hochberg correction, linear regression, and drug-interaction network analysis to characterise interaction frequency and severity. Results: Detailed medical histories over the past year were available for 76 patients. The mean number of drugs prescribed was 9.61 ± 4.47 drugs, with an average of 10.68 ± 10.54 potential interactions per patient. The primary clinical outcome was associated with not respecting certain STOPP-START recommendations (p < 0.01). Overall, 33.1% of NHRs utilised herbal supplements, resulting in a total of 76 potential herb–drug interactions. Conclusions: The results suggest a potential impact of DDIs on clinical outcomes, underscoring the need for further studies to clarify causality. The use of STOPP/START recommendations and deprescribing could lead to better tolerability and smaller drug-related burden in the institutionalised, elderly population. Full article

Phishing detection models often report strong benchmark performance, yet their reliability under realistic deployment conditions remains uncertain. This study examines this problem by investigating three failure modes of cross-dataset phishing email detection: corpus generalization failure, asymmetric prevalence-shift failure, and artifact-driven spurious learning. Using six public email corpora, CEAS_08, Enron, Ling, Nazario, Nigerian Fraud, and SpamAssassin, the study evaluates Term Frequency (TF) and Inverse Document Frequency (IDF)-based Logistic Regression and Linear Support Vector Classifier (SVC) models across pooled baseline testing, single-corpus cross-dataset transfer, leave-one-corpus-out pooled training, prevalence-shift simulation, training prevalence manipulation, dataset-identification analysis, top-feature inspection, artifact-removal ablation, and targeted feature-sensitivity masking. The findings show that single-corpus models are unstable under cross-dataset transfer, with F1-scores varying substantially across source–target combinations. In contrast, leave-one-corpus-out pooled training improves robustness, with Logistic Regression achieving sustained F1-scores between 0.8201 and 0.8994, and Linear SVC achieving F1-scores between 0.7607 and 0.8910 across unseen corpora. Prevalence-shift experiments reveal that failure is asymmetric and threshold-dependent. High-prevalence-trained models maintain high recall under fixed thresholds but suffer sharp recall degradation when operational alert-budget constraints are imposed. Conversely, low-prevalence-trained models become overly conservative in high-threat environments, producing high precision but substantially lower recall and poorer calibration. Artifact analyses further show that source corpus identity is highly learnable, with dataset-identification accuracy reaching 0.9722 for Logistic Regression and 0.9806 for Linear SVC. Top-feature and masking analyses indicate that models rely partly on corpus markers, date tokens, URL/domain terms, headers, and other artifact-like features rather than only general phishing indicators. The study contributes a deployment-aware and adversary-aware evaluation framework for phishing detection. It shows that benchmark accuracy alone is insufficient for assessing real-world robustness and that reliable phishing detection requires cross-corpus validation, prevalence-aware thresholding, and systematic testing for artifact-driven spurious learning. Full article

Virtually all spaceborne topographic lidars to date have used a single beam, with the exception of the ATLAS lidar on NASA’s ICESat-2 satellite, which split the beam into 3 “strong” and 3 “weak” beamlets distributed perpendicular to the along-track path of the satellite. This approach has provided high-resolution along-track surface measurements but relatively poor resolution cross-track measurementswithin a given surface area. The present paper attempts to resolve this discrepancy by (1) transmitting and scanning a single Gaussian beam and (2) imaging the return onto a 14 × 14 pixelated, single-photon sensitive, detector array, thereby providing between 100 and 196 measurements per pulse, depending on the solar background. Besides enhancing the lidar’s capability to penetrate tree canopies and water bodies, the proposed single-beam approach provides one to two orders of magnitude more measurements per pulse with equal spatial resolution in boththe along-track and cross-track directions. At the 10 kHz pulse rate of the ATLAS laser on NASA’s ICESat-2 satellite, this implies between 1 and 2 million topographic measurements per second. The maximum surface area observable by a single pulse increases with the laser peak power defined by the ratio of the pulse energy to the temporal pulsewidth. Larger surface areas per pulse result in more time for cross-track scanning while still maintaining contiguous along-track mapping. Two scanning methods appear to be feasible: (1) circular scans using individual but temporally coordinated wedge scanners for the transmitted and received beams, and (2) unidirectional linear scans utilizing Acousto-Optic Deflectors. The circular scan approach is probably easier to implement, but it also requires additional post-processing to obtain an accurate contiguous 3D image of the planetary terrain. Full article

Nanozymes, nanomaterials that mimic enzymatic activity, offer superior stability, tunability, and lower production costs compared to natural enzymes. To date, most nanozyme-based point-of-care (PoC) diagnostic systems have relied on oxidation reactions, such as oxidation of 3,3′,5,5′-tetramethylbenzidine, which often suffer from limited substrate stability and high background signal. This study investigates reduction reactions, particularly those involving tetrazolium salts, as an alternative route for signal generation in PoC devices. For this purpose, monometallic and bimetallic gold, palladium, and platinum nanoparticles were synthesized via chemical reduction using poly(vinyl alcohol) as a stabilizing agent. The resulting nanoparticles were uniform in size and morphology. Their catalytic performance was confirmed through the reduction of 4-nitrophenol. The tetrazole salts were selected as promising substrates for application in PoC settings and further explored by examining the nanozyme-based reduction of 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT). The nanozymes catalyzed the reduction of MTT in the presence of sodium borohydride, producing a distinct colorimetric signal under selected conditions. The effects of reducing agent concentration, buffer pH, and potential interferents were evaluated, with performance suitable for PoC devices achieved at basic pH and low borohydride concentration. Interference studies showed negligible MTT reduction in the presence of physiological levels of ascorbic acid, human serum albumin, and 10% concentration of human serum. Finally, a proof-of-concept lateral flow assay demonstrated successful signal generation through nanozyme-catalyzed MTT reduction. Results establish tetrazolium salts as suitable substrates for nanozyme-enhanced PoC diagnostics and highlight reduction-based chromogenic systems as a viable alternative to traditional oxidation-based assays. Full article

The visual quality of beverages is a major factor affecting consumers’ perception, quality evaluation, and market acceptance. Traditional colorimetric analysis is accurate but requires specialized equipment, time-consuming sample preparation, and substantial financial and time investment. The objective of this study was to develop a rapid, inexpensive, and accurate alternative method to predict the main color attributes of a date syrup–buttermilk beverage during processing and storage using an artificial neural network (ANN) approach. A multilayer perceptron ANN was developed using a back propagation algorithm. The ANN included three input variables (concentration of date syrup, storage cooling temperature, and storage time), one hidden layer with twenty neurons, and nine output color attributes (lightness, redness/greenness, yellowness/blueness, hue angle, Chroma, total color difference, browning index, whiteness index, and yellow index). To compare the effectiveness of the ANN model for the prediction of color attributes, the multiple linear regression (MLR) models were developed using the same inputs and the same training dataset. Experimental results indicated that all processing variables and their interactions had a significant effect on the color attributes of the beverage (p < 0.001). The trained ANN model exhibited excellent prediction capacity during the validation phase with high coefficients of determination (R² range was between 0.9974 and 0.9997) with lower root mean squared error than MLR. Moreover, sensitivity analysis indicated date syrup concentration as the most influential factor on the final color profile. The developed ANN model provides an effective approach for the offline prediction of color quality during processing and storage under laboratory conditions. Although the integration of the ANN model with inline sensors may offer opportunities for future intelligent quality-control applications, real-time implementation and industrial deployment were not evaluated in the present study. Full article

Does mandatory sustainability disclosure improve the quality of corporate financial reporting immediately, gradually, or with delay? We address this question using Saudi Arabia’s January 2021 Tadawul ESG Disclosure Guidelines—the first comprehensive sustainability disclosure framework in the Gulf Cooperation Council and a uniform, accurately dated regulatory shock affecting all listed firms. Using a balanced panel of 135 non-financial firms over 2017–2024 (1080 firm-year observations), we estimate absolute discretionary accruals from the Modified Jones Model and employ event-time fixed-effects regressions with Driscoll–Kraay standard errors robust to heteroskedasticity, autocorrelation, and cross-sectional dependence. We document a temporal paradox: reporting quality did not change in the announcement year (2021), deteriorated significantly in 2022 (+28%) and 2023 (+38%) relative to the pre-reform baseline, and then improved significantly in 2024 (−17%). The pattern survives performance-matched discretionary accruals, exclusion of the 2020 COVID-19 year, a placebo test, sectoral disaggregation across nine Tadawul-aligned industry groups, and a battery of pre-reform firm characteristics. Heterogeneity analysis identifies the underlying mechanism: voluntary pre-2021 ESG disclosers and firms with stronger pre-reform governance exhibit amplified short-run deterioration, while larger firms with pre-existing reporting infrastructure show a substantially attenuated paradox. These patterns are jointly consistent with the adjustment-cost mechanism we develop: the reform redirected scarce reporting governance toward the new disclosure margin during a three-year compliance buildout, after which the constraining effect on accrual-based earnings management emerged. The findings carry direct implications for the design and evaluation of mandatory sustainability disclosure reforms currently advancing across emerging and developed markets. Full article

This paper investigates how generative AI produces and propagates hallucinated academic references, focusing on the recurring non-existent citation “Education Governance and Datafication” attributed to Ben Williamson and Nelli Piattoeva. Drawing on 196 accessible source papers identified through Google Scholar and Google searches, the study analyses the structure, recurrence, and onward citation of this phantom reference. It shows that hallucinated citations are not random inventions but patterned re-combinations of real authors, journals, dates, and keywords, with duplication occurring in nearly 30% of these hallucinated citations. The paper also reports a structured interrogation of ChatGPT 5-mini about how it generates citations and finds that, absent of verification, the model reconstructs plausible references from learned patterns rather than factual recall. Finally, 110 AI-generated essays on datafication and school governance were examined: while most references were genuine or partly accurate, 29.8% remained fully hallucinated citations, including exact matches to the most common phantom citation, and an additional 29% were partially hallucinated citations. The findings highlight ongoing risks to academic integrity and show that web-enabled AI still does not fully eliminate fabricated references. Full article

Takotsubo syndrome (TTS) is an acute disorder characterized by transient left ventricular dysfunction with typical regional wall motion abnormalities, most commonly apical ballooning. It accounts for 1–3% of all suspected acute coronary syndromes and up to 5–6% in women presenting with ST-segment elevation myocardial infarction requiring coronary angiography to exclude obstructive coronary artery disease. The pathophysiology of TTS is complex and not fully elucidated, with sympathetic hyperactivation playing a central role through calcium dysregulation, oxidative stress, and metabolic alterations. Both clinical and experimental data demonstrate the importance of inflammation, with cell infiltration and persistent immune activation exceeding the acute phase. Increasing evidence highlights the impact of coronary microvascular disfunction (CMVD) as a secondary phenomenon, with some findings that support its role as a causative substrate. Beyond well-known predisposing conditions such as female sex, postmenopausal age, and neurological and psychiatric disorders with the trigger of a physical or psychological event, numerous case reports associate the syndrome with chronic autoimmune diseases, even if clear experimental evidence remains poor and worthy of further study. Echocardiography and advanced imaging techniques, including cardiac magnetic resonance and positron emission tomography, have provided insights into transient CMVD, reversible myocardial edema, and metabolic impairment, strengthening our knowledge of the syndrome as a dynamic process. It is also of growing interest to perform invasive hemodynamic assessment to explain the increase in microvascular resistance. This review offers a comprehensive and up-to-date overview of these techniques in the context of TTS. Since clinically, TTS may be associated with significant morbidity and mortality, with some unexplained cases of long-term myocardial disfunction or even recurrence, a deeper understanding of the interplay between catecholamines, inflammation, immune substrate, and CMVD may improve risk stratification and lead to the development of targeted therapeutic strategies. Full article

Adhesive dentistry has undergone a significant evolution, transitioning from classical multi-step adhesives to simplified single-bottle or universal adhesives and now towards self-adhesive composites that no longer require a separate adhesive. This review focused on clinical applications, recent developments, and future trends in peer-reviewed articles identified through database searches in PubMed, Web of Science Core Collection, EBSCO DOSS, and Google Scholar without date restrictions. Reference mining of the identified articles was also used. Significant advances in the clinical performance of simplified adhesives are challenging the status of “gold standard” adhesives, although their long-term reliability in load-bearing (Class II) composite restorations remains uncertain due to a lack of longitudinal real-world data and extended survival metrics. Integration of acidic functional monomers like 10-MDP is becoming a standard to create a more stable chemical bond with dentin hydroxyapatite, rather than relying solely on micromechanical retention. Ensuring long-term stability of the hybrid layer against degradation remains a challenge. When enamel is present, etching with phosphoric acid is still recommended, while the necessity of enamel beveling is being questioned. As the clinical success of self-adhesive flowable composites is limited to non-load-bearing areas, further developments are moving toward self-adhesive bioactive composites for bulk-filling that combine self-adhesive properties with load-bearing capacity. Full article

JC polyomavirus (JCPyV) is a worldwide-distributed human virus. Primary infection with JCPyV is usually asymptomatic and followed by a lifelong persistent infection. In situations of profound immunosuppression or prolonged treatment with specific immunomodulatory drugs, such as natalizumab, viral reactivation can occur and lead to the development of JCPyV-associated diseases. Progressive multifocal leukoencephalopathy (PML), a severe demyelinating disease of the central nervous system, is the most common clinical manifestation of JCPyV reactivation. Less frequently, viral reactivation may be associated with granule cell neuronopathy, encephalopathy, and meningitis. However, the pathogenesis of these diseases remains a subject of debate. To date, no treatment is available for JCPyV infection. Nevertheless, some therapeutic options have been explored. Despite its ubiquity, the main mode of JCPyV transmission remains unclear. Epidemiological data suggests that primary infection may be acquired in childhood and throughout life, with the involvement of different routes of transmission. In the absence of an effective treatment, the prevention of infection is crucial in risk groups, such as immunosuppressed or natalizumab-treated patients. Therefore, until the achievement of an effective antiviral molecule or a prophylactic vaccine, prevention measures will rely on avoiding transmission, for which it is crucial to understand how transmission occurs. The present review emphasizes the current data on JCPyV transmission routes and associated diseases, including pathogenesis, diagnosis and potential treatment options, highlighting the importance of further studies. Full article

The Ediacaran Dengying Formation 2nd Member (hereafter 2nd Member) in the Sichuan Basin is influenced by major tectonic events including the Caledonian, Indosinian, and Himalayan orogenies and this strata has experienced a complex hydrocarbon accumulation history, resulting in inconsistent gas–water contacts. To elucidate this complex history, this study investigates the diagenetic mineral filling sequence within the Dengying 2nd Member in the Penglai area. We integrated data from analytical techniques such as cathodoluminescence (CL), in situ trace element analysis, U–Pb geochronology, and fluid-inclusion microthermometry. Based on these analyses, this study established the paragenetic sequence, incorporating both diagenesis and hydrocarbon accumulation, for the Dengying 2nd Member. This sequence comprises eight distinct phases of mineral precipitation and hydrocarbon emplacement: fibrous dolomite, granular dolomite, fine crystalline dolomite, first-phase bitumen, medium crystalline dolomite, saddle dolomite, second-phase bitumen, and quartz. From this sequence, we propose a four-stage hydrocarbon accumulation model for the Dengying Formation: (1) primary migration and accumulation during the Indosinian period; (2) oil cracking to gas during the Yanshanian period; and (3) and (4) two distinct stages of gas pool adjustment during the Himalayan period. Corresponding to these stages, this study developed distinct accumulation models and simulated migration and accumulation processes during key stages. The results indicate that the distribution of paleo-oil pools exerts significant control over the location of present-day gas accumulations. Initial oil charge was controlled by the distribution of carrier beds and hydrocarbon charging pathways, with water zones observed more frequently in the lower intervals of the Dengying 2nd Member. Subsequently, gas generated from oil-cracking filled these carrier beds, with areas of gas enrichment correlating with zones of high paleo-oil saturation. Finally, during the later adjustment stages, fault activity induced gas remigration and leakage, significantly impacting the final trapping configuration and preservation of gas accumulations. Full article

The No. VI ore block of the Galinge skarn system in the Qimantagh metallogenic belt, East Kunlun, contains proximal Fe-oxide mineralization and distal Pb–Zn sulfide mineralization that are spatially zoned and locally overprinted along faults and interlayer fracture zones. To constrain the controls on Fe–Pb–Zn zonation and overprinting within this ore block, we integrated LA–ICP–MS zircon U–Pb dating, zircon Lu–Hf isotopes, whole-rock major and trace elements, and in situ trace elements of magnetite, pyrite, chalcopyrite, pyrrhotite, and arsenopyrite. Zircon U–Pb ages indicate two Indosinian intrusive pulses: an early granodiorite at 235.1 ± 0.51 Ma and a younger granodiorite–quartz diorite at 229.52 ± 0.46 Ma. Excluding the hydrothermally altered sample ZK26804-805, the intrusive rocks are metaluminous, medium- to high-K calc-alkaline I-type granitoids mainly derived from remelting of ancient crustal material, with a greater juvenile crustal or mantle contribution in the younger phase. Magnetite is generally Zn-rich and Pb-poor, whereas late pyrite and chalcopyrite are enriched in Pb, Ag, Cd, and Bi; local Sb–As anomalies in magnetite and arsenopyrite indicate late hydrothermal overprinting. The Fe and Pb–Zn mineralization is best interpreted as staged products of one multipulse magmatic–hydrothermal system controlled not only by intrusive pulses but also by inherited structural pathways, host-rock reactivity, and evolving redox-sulfidation conditions. The interpretation of Sb–As enrichment in magnetite is therefore used cautiously because these elements may occur as lattice substitutions and/or micro- to nano-inclusions introduced or modified during retrograde alteration. Full article

Chemotherapy has been used in cancer treatment for decades; however, standard chemotherapy treatments still have significant weaknesses, including collateral damage to healthy tissue, rapid development of drug resistance, and dose-limiting toxicity that limits therapeutic value. There is now an alternative approach using polymer materials that are responsive to biological stimuli that will allow for improved treatment of cancer while avoiding the limitations. Responsive polymer materials are designed to be inert during circulation until they reach their site of action; then, they will respond to specific triggers. These smart carriers respond to stimuli present in the tumor microenvironment (e.g., low pH, high glutathione levels, and increased proteolytic activity) or external stimuli applied at the bedside (e.g., localized heat, light, ultrasound, and applied magnetic fields). In both cases, there is a consistent pattern where the drug is released exactly where/when it is needed, with minimal drug release occurring outside that location and timeframe. Therefore, it is theorized that the use of polymeric-based delivery systems with stimuli-regulated drug release will significantly increase the concentration of drug delivered intratumorally, decrease the drug toxicity, and provide a potential mechanism to overcome the development of multidrug resistance from a variety of cancer treatments. To date, various types of responsive polymers have been developed and could be combined to give rise to a wide variety of different vehicle systems (e.g., micelles, nanogels, hydrogels, and hybrid delivery systems), with many of these carriers designed to respond to multiple stimuli simultaneously. Nonetheless, significant challenges remain in the clinical application of these materials due to tumor heterogeneity, immune system interactions, reproducibility issues, polymer chemistry advances, surface chemistry, and other interaction mechanisms. As a result of all of these evolving regulatory systems, as well as some of the emerging areas of polymer chemistry and surface engineering, theranostic integration will allow for new routes to provide therapy for patients with cancer. Additionally, because of these scientific advances, there will also be more opportunities to provide targeted, controllable, and on-demand treatments to patients using stimuli-responsive polymers. Full article

Artificial intelligence (AI) technologies, which are being actively developed in modern medicine today, increase the speed and quality of patient care. This article mainly seeks to demonstrate the use of various options of computer analysis of clinical images to solve practical problems of increasing the efficiency of routine diagnostics using retrospective analysis, as well as show the potential for its widespread implementation (due to the scalability of the architecture) in practical healthcare, exemplified by ultrasound (US) and magnetic resonance imaging (MRI) data analysis. This is an interuniversity study, its research protocol was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the local Ethics Committee of Orel State University named after I. S. Turgenev (Protocol No. 25 dated 16 November 2022). The software was developed using Python 3.7 and open neural network models. Statistical processing included an efficiency assessment for which IBM SPSS Statistics 20.0 was used. Detection errors in the analysis of 550 US cases did not exceed 6–8% and were associated with technical difficulties due to image quality. When studying 1030 MRI studies, only 0.19% of cases failed to obtain reliable image analysis results. The differences in the average values for the dimensional characteristics of the studied vessels were 0.11–0.12 mm. The effectiveness of AI in clinical tasks is presented. The improvement in segmentation accuracy was achieved through the use of step-by-step image optimization during the AI training stage. The evolution of technologies in medicine, aimed at digitalization and personalization, is intended to improve the quality and speed of studying images in practical work. Full article